Artificial Neural Networks in Pattern Recognition

7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28–30, 2016, Proceedings

  • Friedhelm Schwenker
  • Hazem M. Abbas
  • Neamat El Gayar
  • Edmondo Trentin

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9896)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 9896)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Invited Papers

    1. Front Matter
      Pages 1-1
    2. Luca Pasa, Alessandro Sperduti
      Pages 3-17
    3. Vivienne Breen, Nikola Kasabov, Peng Du, Stefan Calder
      Pages 18-25
  3. Learning Algorithms and Architectures

    1. Front Matter
      Pages 27-27
    2. Alexander Kuleshov, Alexander Bernstein
      Pages 55-67
    3. Jian Hou, Weixue Liu, Xu E
      Pages 80-91
    4. Yann Soullard, Sébastien Destercke, Indira Thouvenin
      Pages 92-104
    5. Lyn-Rouven Schirra, Florian Schmid, Hans A. Kestler, Ludwig Lausser
      Pages 105-116
    6. João Papa, Danillo Pereira, Alexandro Baldassin, Xin-She Yang
      Pages 126-137
    7. Gustavo Rosa, João Papa, Kelton Costa, Leandro Passos, Clayton Pereira, Xin-She Yang
      Pages 138-149
    8. Baptiste Wicht, Andreas Fischer, Jean Hennebert
      Pages 163-174
    9. Vincenzo Lomonaco, Davide Maltoni
      Pages 175-184
    10. Kaspar Riesen, Andreas Fischer, Horst Bunke
      Pages 185-194
  4. Applications

    1. Front Matter
      Pages 195-195

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2016, held in Ulm, Germany, in September 2016.

The 25 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 32 submissions for inclusion in this volume. The workshop will act as a major forum for international researchers and practitioners working in all areas of neural network- and machine learning-based pattern recognition to present and discuss the latest research, results, and ideas in these areas.

 

Keywords

image segmentation machine learning object detection optimization recurrent neural network active learning constrained learning deep learning dimensionality reduction ensemble models imprecise probabilities incremental learning linear dynamical systems personalised modeling semi-supervised learning spiking neural network supervised learning support vector machines time series classification unsupervised learning

Editors and affiliations

  • Friedhelm Schwenker
    • 1
  • Hazem M. Abbas
    • 2
  • Neamat El Gayar
    • 3
  • Edmondo Trentin
    • 4
  1. 1.Ulm UniversityUlmGermany
  2. 2.Ain Shams University CairoEgypt
  3. 3.Cairo University OrmanEgypt
  4. 4.Universitá di Siena SienaItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-46182-3
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-46181-6
  • Online ISBN 978-3-319-46182-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book